Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A system for selecting a bottomhole assembly (BHA), comprising: a computing device comprising a computing processor executing instructions to perform, prior to drilling: executing a first simulation of a first BHA that includes at least a drill bit, a measurement sensor, and a stabilizer, the first simulation generating a first set of performance data that includes at least a predicted measurement quality of the measurement sensor as a function of reproduceability, and the computing device comprising a graphical user interface executing on the computer processor with functionality to perform, prior to drilling: inputting a selected drilling criteria, the selected drilling criteria including at least a measurement quality criteria for the measurement sensor, presenting, on the graphical user interface, the first set of performance data from the first simulation, and selecting a BHA based on a comparison of the first set of performance data and the selected drilling criteria, the comparison including a comparison of the measurement quality criteria of the measurement sensor to the predicted measurement quality of the measurement sensor.
The system is designed for selecting an optimal bottomhole assembly (BHA) configuration for drilling operations. The BHA includes components such as a drill bit, measurement sensors, and stabilizers. The system addresses the challenge of ensuring measurement quality during drilling by simulating BHA performance before actual drilling begins. A computing device executes simulations of different BHA configurations, generating performance data that includes predicted measurement quality metrics, such as reproducibility of sensor readings. Users interact with a graphical user interface to input drilling criteria, including specific measurement quality requirements for the sensors. The system then compares the simulated performance data against these criteria, allowing users to select a BHA configuration that meets the desired measurement quality standards. This approach ensures that the chosen BHA will provide reliable sensor data during drilling, improving operational efficiency and accuracy. The system automates the selection process by leveraging simulation data and user-defined criteria, reducing the need for trial-and-error adjustments during drilling.
2. The system of claim 1 , wherein generating the first set of performance data includes generating the predicted measurement quality as a function of at least one of a collar deflection angle and a lateral displacement at the measurement sensor location.
A system for monitoring and analyzing performance data in industrial or mechanical applications, particularly for rotating machinery, addresses challenges in accurately assessing measurement quality under dynamic conditions. The system generates performance data by predicting measurement quality based on operational parameters such as collar deflection angle and lateral displacement at the sensor location. These parameters influence the accuracy and reliability of measurements taken by the sensor, which may be mounted on or near rotating components. By accounting for these factors, the system improves the precision of performance assessments, enabling better maintenance decisions and operational efficiency. The system may also include additional features such as real-time data processing, historical trend analysis, and predictive modeling to further enhance monitoring capabilities. The integration of deflection and displacement data ensures that measurements are corrected or adjusted for environmental and mechanical disturbances, reducing errors in performance evaluations. This approach is particularly useful in applications where sensors are subjected to varying loads, vibrations, or misalignments, such as in turbines, pumps, or other rotating equipment. The system's ability to dynamically adjust for these factors ensures consistent and reliable performance data, supporting proactive maintenance and reducing downtime.
3. The system of claim 1 , wherein the computing device further comprises the computing processor executing instructions to perform: executing a second simulation of a second BHA that includes at least one drill bit, a measurement sensor, and a stabilizer, the second simulation generating a second set of performance data, and wherein the computing device further comprises the graphical user interface executing on the computer processor with functionality to perform: modifying, based on the first set of performance data, at least one parameter selected from the group consisting of BHA parameters, wellbore parameters, and the drilling operating parameters, wherein modifying involves changing a value of the at least one parameter to obtain a modified parameter, presenting, on the graphical user interface, the second set of performance data from the second simulation, the second simulation based on the modified parameter, and selecting a BHA based on the first set of performance data, the second set of performance data, and the selected drilling criteria.
This invention relates to a system for optimizing bottomhole assembly (BHA) configurations in drilling operations. The system addresses the challenge of selecting efficient BHA designs by simulating performance under varying conditions and comparing results to select the best configuration. The system includes a computing device with a processor that executes simulations of BHAs, each comprising at least one drill bit, a measurement sensor, and a stabilizer. The first simulation generates performance data based on initial parameters, such as BHA design, wellbore conditions, and drilling operations. The system then modifies these parameters—such as BHA geometry, wellbore trajectory, or drilling speed—to generate a second simulation with updated performance data. A graphical user interface displays both sets of performance data, allowing users to compare results and select the optimal BHA configuration based on predefined drilling criteria, such as efficiency, stability, or cost. The system enables iterative testing of different BHA designs and operational parameters, providing data-driven insights to improve drilling performance. By simulating and comparing multiple configurations, users can make informed decisions to enhance drilling efficiency and reduce operational risks.
4. The system of claim 3 , wherein presenting further comprises: visualizing, on the graphical user interface, at least one selected from the group consisting of the first set of performance data and the second set of performance data.
The system displays performance data on the screen, choosing from a first set of data or a second set of data, or both.
5. The system of claim 3 , wherein the first and second sets of performance data comprise performance results of the first BHA indicative of at least one selected from the group consisting of a steerability of the BHA, stability of the BHA, and robustness of the BHA.
A system for evaluating the performance of a bottomhole assembly (BHA) used in drilling operations monitors and analyzes data from the BHA to assess its operational characteristics. The system collects performance data from the BHA, including measurements related to its steerability, stability, and robustness. Steerability refers to the BHA's ability to change direction during drilling, stability refers to its ability to maintain consistent drilling conditions, and robustness refers to its durability and resistance to failure under drilling stresses. The system processes this data to generate insights into the BHA's performance, enabling operators to optimize drilling operations and improve efficiency. By analyzing these performance metrics, the system helps identify potential issues early, reducing downtime and enhancing drilling accuracy. The data may be collected from sensors embedded in the BHA or from external monitoring systems, and the analysis may involve comparing the performance data against predefined benchmarks or historical data to assess deviations and trends. This system is particularly useful in oil and gas drilling, where precise control and reliability of the BHA are critical for successful operations.
6. The system of claim 5 , wherein steerability of the BHA comprises at least one selected from the group consisting of buildup rate and dogleg severity.
The system relates to directional drilling, specifically improving the steerability of a bottomhole assembly (BHA) in oil and gas drilling operations. The problem addressed is the need for precise control over the BHA's trajectory to navigate complex geological formations while maintaining drilling efficiency. The system enhances steerability by adjusting at least one of two key parameters: buildup rate and dogleg severity. Buildup rate refers to the rate at which the wellbore angle changes relative to the vertical, while dogleg severity measures the sharpness of the wellbore's curvature. By controlling these parameters, the system enables more accurate directional adjustments, reducing the risk of wellbore instability and improving drilling accuracy. The system likely integrates sensors, actuators, and control algorithms to monitor and modify these parameters in real time, ensuring optimal steering performance. This capability is particularly valuable in extended-reach drilling and horizontal well applications, where precise trajectory control is critical. The invention builds on prior art by focusing on specific steerability metrics to enhance directional drilling performance.
7. The system of claim 5 , wherein stability of the BHA comprises at least one selected from the group consisting of axial, lateral, and rotational vibrations.
A system for stabilizing a bottomhole assembly (BHA) in drilling operations addresses the problem of unwanted vibrations that can damage drilling equipment and reduce efficiency. The system includes a BHA with a drill bit and a stabilization mechanism designed to mitigate vibrations during drilling. The stabilization mechanism can be integrated into the BHA or attached as a separate component. It may include active or passive stabilization features, such as hydraulic dampers, adjustable stabilizers, or vibration sensors that detect and counteract vibrations in real time. The system monitors and controls vibrations in multiple axes, including axial (along the drill string), lateral (side-to-side), and rotational (torsional) vibrations, to ensure stable drilling performance. By reducing these vibrations, the system extends the lifespan of drilling components, improves drilling accuracy, and enhances overall operational efficiency. The stabilization mechanism may also include feedback systems that adjust stabilization parameters based on real-time data to adapt to changing drilling conditions. This approach ensures consistent performance and minimizes downtime caused by vibration-related failures.
8. The system of claim 5 , wherein robustness of the BHA comprises at least one selected from the group consisting of bending moments, torques, axial force, stress, vibrations, contact forces, and buckling.
A system for enhancing the robustness of a bottomhole assembly (BHA) in drilling operations is disclosed. The BHA is designed to withstand various mechanical stresses and environmental conditions encountered during drilling. The system monitors and evaluates multiple parameters to ensure structural integrity and operational reliability. These parameters include bending moments, torques, axial forces, stress levels, vibrations, contact forces, and buckling. By assessing these factors, the system can detect potential failures or performance degradation, allowing for preventive maintenance or adjustments to drilling operations. The BHA may incorporate sensors or other measurement devices to collect real-time data on these parameters. The system may also include control mechanisms to adjust drilling parameters, such as weight-on-bit or rotational speed, to mitigate excessive stress or damage. The overall goal is to improve drilling efficiency, reduce downtime, and extend the lifespan of the BHA by proactively managing mechanical loads and environmental conditions.
9. The system of claim 1 , wherein generating the first set of performance data includes determining the predicted measurement quality of the measurement sensor based on sag of the BHA at the measurement sensor location.
The invention relates to a system for evaluating measurement quality in a borehole assembly (BHA) used in drilling operations. The system addresses the challenge of ensuring accurate measurements from sensors deployed in a BHA, where mechanical deformations such as sag can degrade data reliability. The system generates performance data for measurement sensors by analyzing the predicted measurement quality, which is influenced by the sag of the BHA at the sensor's location. Sag refers to the bending or deflection of the BHA due to gravitational forces, drilling dynamics, or other factors, which can introduce errors in sensor readings. By assessing sag at the sensor's position, the system quantifies how much the BHA's deformation affects measurement accuracy. This allows operators to identify potential data inaccuracies and adjust drilling parameters or sensor placement to improve measurement reliability. The system may also integrate additional performance metrics, such as sensor calibration data or environmental conditions, to provide a comprehensive evaluation of measurement quality. The goal is to enhance the precision of downhole measurements, which are critical for navigation, formation evaluation, and drilling efficiency.
10. The system of claim 1 , wherein generating the first set of performance data includes determining the predicted measurement quality of the measurement sensor based on drill string deformation at the measurement sensor location.
The invention relates to oil and gas drilling systems that monitor wellbore conditions using measurement sensors attached to a drill string. A key challenge in such systems is ensuring accurate measurements, as drill string deformation (e.g., bending or vibration) can distort sensor readings. The system addresses this by generating performance data for the measurement sensor, including a predicted measurement quality metric. This metric is derived by analyzing drill string deformation at the sensor's specific location, accounting for factors like drill string dynamics, environmental conditions, and sensor positioning. The system may also compare this predicted quality against predefined thresholds to assess reliability. By correlating deformation data with sensor performance, the system improves measurement accuracy and reliability in real-time drilling operations. Additional features may include adjusting sensor calibration or triggering alerts based on deformation-induced errors. The invention enhances drilling efficiency by ensuring high-quality data for decision-making, such as steering corrections or formation evaluation.
11. The system of claim 1 , wherein generating the first set of performance data includes determining the predicted measurement quality of the measurement sensor based on drill string bending at the measurement sensor location.
The invention relates to a system for evaluating measurement quality in drilling operations, specifically addressing the challenge of ensuring accurate sensor data in the presence of drill string bending. The system generates performance data for a measurement sensor by analyzing the predicted measurement quality, which is influenced by the bending of the drill string at the sensor's location. This involves assessing how structural deformations of the drill string, such as bending, impact the reliability and accuracy of measurements taken by the sensor. The system may also include a measurement sensor configured to collect data from a drill string during drilling operations, and a processing unit that processes this data to generate performance metrics. The processing unit may further compare the predicted measurement quality against predefined thresholds to determine if the sensor data is reliable. The system may also include a communication interface to transmit the performance data to a remote monitoring system for real-time analysis. By accounting for drill string bending, the system improves the accuracy and reliability of sensor measurements in drilling applications.
12. The system of claim 1 , wherein generating the first set of performance data includes determining the predicted measurement quality of the measurement sensor based on spacing from magnetic components.
A system for optimizing sensor performance in industrial or automotive applications addresses the challenge of ensuring accurate measurements in environments with magnetic interference. The system includes a measurement sensor, a processor, and a memory storing instructions for generating performance data. The sensor collects operational data, such as temperature, pressure, or vibration, in proximity to magnetic components like motors or actuators. The processor analyzes this data to predict measurement quality based on the sensor's distance from these magnetic sources. By assessing spacing, the system determines how magnetic interference may degrade sensor accuracy, allowing for adjustments to sensor placement or calibration to mitigate errors. The system may also compare predicted quality against thresholds to trigger alerts or corrective actions. This approach improves reliability in applications where magnetic fields could otherwise distort readings, such as in electric vehicle powertrains or industrial machinery monitoring. The system may further integrate with diagnostic tools to provide real-time feedback on sensor health and environmental conditions.
13. The system of claim 1 , wherein generating the first set of performance data includes determining the predicted measurement quality of the measurement sensor as a function of nearness to a borehole wall.
This invention relates to a system for evaluating measurement sensor performance in a borehole environment, particularly focusing on the impact of sensor proximity to the borehole wall on measurement quality. The system generates performance data by analyzing the predicted measurement quality of a sensor based on its distance from the borehole wall. This involves assessing how variations in sensor position affect accuracy, reliability, or other quality metrics of the measurements. The system may also include components for deploying the sensor, collecting raw measurement data, and processing this data to derive performance insights. The core innovation lies in dynamically adjusting or optimizing sensor placement to improve measurement quality by accounting for the nearness to the borehole wall, which can introduce environmental or physical interference. This approach ensures more accurate and reliable data collection in subsurface exploration or drilling operations. The system may further integrate with other subsurface monitoring tools to enhance overall data integrity and operational efficiency.
14. The system of claim 1 , wherein generating the first set of performance data includes determining the predicted measurement quality of the measurement sensor in a static survey condition.
A system for evaluating measurement sensor performance in static survey conditions is disclosed. The system addresses the challenge of assessing sensor accuracy and reliability when deployed in static environments, where factors like environmental noise, calibration drift, and sensor degradation can impact measurement quality. The system generates performance data by analyzing sensor outputs under controlled static conditions, where the sensor remains stationary and measurements are taken over time. This includes determining the predicted measurement quality, which involves evaluating metrics such as signal stability, noise levels, and consistency of readings. The system may also compare these metrics against predefined thresholds or historical data to identify deviations or anomalies. By quantifying measurement quality in static conditions, the system enables early detection of sensor degradation, calibration errors, or environmental interference, improving overall measurement reliability. The performance data can be used for sensor validation, maintenance scheduling, or system diagnostics. The system may integrate with other components, such as data acquisition modules or calibration tools, to provide a comprehensive assessment of sensor health and accuracy.
15. The system of claim 1 , wherein generating the first set of performance data includes determining the predicted measurement quality of the measurement sensor in a real-time survey condition.
This invention relates to a system for evaluating the performance of measurement sensors, particularly in real-time survey conditions. The system addresses the challenge of accurately assessing sensor performance in dynamic environments where conditions may vary, impacting measurement quality. The system generates performance data by determining the predicted measurement quality of the sensor under real-time survey conditions. This involves analyzing factors such as environmental variables, sensor calibration, and operational parameters to estimate how well the sensor will perform. The system may also compare the predicted quality against predefined thresholds or historical data to identify deviations or potential issues. Additionally, the system can adjust sensor settings or trigger alerts based on the performance data to ensure reliable measurements. The invention improves the accuracy and reliability of sensor-based surveys by providing real-time insights into measurement quality, allowing for proactive adjustments and minimizing errors in data collection. This is particularly useful in applications like environmental monitoring, industrial inspections, or scientific research where precise and consistent measurements are critical.
16. The method of claim 1 , wherein inputting the selected drilling criteria comprises entering a rate of penetration as a dynamic input that is allowed vary to during at least the first simulation.
This invention relates to a method for optimizing drilling operations in the oil and gas industry, specifically focusing on adjusting drilling parameters in real-time simulations to improve efficiency and accuracy. The problem addressed is the need for dynamic adjustments in drilling criteria, such as rate of penetration (ROP), to account for changing subsurface conditions and optimize drilling performance. The method involves simulating drilling operations using predefined criteria, including geological data and drilling constraints. A key feature is the ability to input and modify drilling criteria dynamically during the simulation. Specifically, the rate of penetration (ROP) can be adjusted in real-time as the simulation progresses, allowing for iterative testing of different drilling scenarios. This dynamic input capability enables operators to assess how variations in ROP affect drilling outcomes, such as time, cost, and risk, under varying subsurface conditions. The method may also include additional features, such as visualizing simulation results, comparing multiple scenarios, and integrating real-time data to refine predictions. By allowing ROP to vary during the simulation, the method provides a more flexible and accurate approach to planning and optimizing drilling operations, reducing uncertainties and improving decision-making. This dynamic adjustment capability is particularly useful in complex geological formations where drilling conditions can change rapidly.
17. The method of claim 1 , further comprising: generating a model of the first BHA, wherein executing the first simulation of the first BHA comprises simulating drilling through a model of a subterranean formation using the first model of the first BHA; and adjusting the model of the first BHA based on the first set of performance data from the first simulation, wherein selecting comprises selecting the first BHA after the adjustment to the model of the first BHA.
This invention relates to optimizing bottomhole assembly (BHA) designs for drilling operations in subterranean formations. The problem addressed is the need to improve drilling efficiency and performance by simulating and refining BHA configurations before physical implementation. The method involves creating a digital model of a BHA and simulating its performance while drilling through a modeled subterranean formation. The simulation generates performance data, which is used to adjust the BHA model iteratively. This iterative process refines the BHA design to optimize drilling parameters such as stability, durability, and efficiency. The refined BHA model is then selected for actual drilling operations based on the simulation results. The simulation may include factors like formation properties, drilling dynamics, and BHA component interactions. Adjustments to the BHA model may involve modifying component specifications, configurations, or operational parameters. The goal is to ensure the selected BHA design performs optimally under the expected drilling conditions, reducing risks and improving drilling outcomes. This approach minimizes trial-and-error in physical testing and enhances drilling precision and cost-effectiveness.
18. The method of claim 1 , wherein presenting comprises displaying the first set of performance data at least partially as a function of length of the first BHA, wherein selecting comprises receiving an input to add, remove, or move one or more components of the BHA along the length of the BHA.
This invention relates to a method for optimizing the design of a bottomhole assembly (BHA) used in drilling operations, particularly for improving performance visualization and component adjustment. The BHA is a critical part of a drilling system, and its design significantly impacts drilling efficiency, stability, and cost. The challenge addressed is the lack of intuitive tools for visualizing how BHA performance metrics vary along its length and for dynamically modifying its configuration to enhance performance. The method involves displaying performance data of the BHA as a function of its length, allowing users to assess how different sections of the assembly contribute to overall performance. This visualization helps identify inefficiencies or potential improvements. Users can interact with the system by adding, removing, or repositioning BHA components along its length, enabling real-time adjustments to optimize performance. The system may also incorporate additional features, such as simulating drilling conditions or comparing multiple BHA configurations, to further assist in design refinement. By providing a clear, length-based representation of performance data and an interactive interface for component manipulation, this method streamlines the BHA design process, reducing trial-and-error iterations and improving drilling efficiency. The approach is particularly useful in oil and gas exploration, where precise BHA optimization can lead to significant cost savings and operational benefits.
19. The method of claim 1 , whereby the selected BHA is built and used to drill a well through a formation.
A method for drilling a well through a formation involves selecting a bottomhole assembly (BHA) based on formation characteristics and drilling objectives. The BHA is designed to optimize drilling efficiency, stability, and performance. The selected BHA includes components such as drill bits, stabilizers, and measurement tools tailored to the specific geological conditions of the formation. The method ensures the BHA is built and deployed to drill the well effectively, addressing challenges like formation hardness, pressure, and drilling fluid compatibility. The process may involve real-time monitoring and adjustments to the BHA configuration to maintain optimal drilling conditions. The method aims to improve drilling speed, reduce tool wear, and enhance wellbore quality by using a customized BHA for the given formation.
20. A system for selecting a bottomhole assembly (BHA), comprising: a computing device comprising a computing processor executing instructions to perform: executing a first simulation without drilling of a first BHA that includes at least a drill bit, a measurement sensor, and a stabilizer, the first simulation generating a first set of performance data that includes at least a predicted measurement quality of the measurement sensor of the first BHA as a function of reproduceability; executing a second simulation without drilling of a second BHA that includes at least a drill bit, a measurement sensor, and a stabilizer, the second simulation generating a second set of performance data that includes at least a predicted measurement quality of the measurement sensor of the second BHA as a function of reproduceability, and the computing device comprising a graphical user interface executing on the computer processor with functionality to perform: receiving a selected drilling criteria; presenting, on the graphical user interface, the first set of performance data from the first simulation; presenting, on the graphical user interface, the second set of performance data from the second simulation; and selecting the first BHA or the second BHA prior to drilling based on a comparison of the first set of performance data and the selected drilling criteria, the comparison including at least a comparison of the predicted measurement quality of the measurement sensor of the first BHA and the predicted measurement quality of the measurement sensor of the second BHA.
The system is designed for selecting an optimal bottomhole assembly (BHA) configuration for drilling operations. The problem addressed is the challenge of predicting the performance of different BHA configurations before drilling begins, particularly in terms of measurement quality and reproducibility. The system uses a computing device to simulate the performance of multiple BHA configurations without requiring physical drilling. Each BHA includes at least a drill bit, a measurement sensor, and a stabilizer. The system executes simulations for each BHA configuration, generating performance data that includes predicted measurement quality as a function of reproducibility. A graphical user interface allows users to input drilling criteria and compare the performance data of different BHA configurations. The system then selects the most suitable BHA based on the comparison of predicted measurement quality and other performance metrics against the specified drilling criteria. This approach enables operators to make informed decisions about BHA selection before drilling begins, improving efficiency and reducing risks associated with suboptimal configurations.
21. The system of claim 20 , wherein generating the first and second sets of performance data includes determining predicted measurement quality based on at least one of BHA sag, drill string deformation, drill string bending, or spacing from magnetic components at the measurement sensor location.
This invention relates to a system for improving the accuracy of downhole measurements in drilling operations, particularly addressing challenges in measurement quality due to environmental and mechanical factors. The system generates performance data for downhole sensors by analyzing predicted measurement quality, which is influenced by factors such as bottomhole assembly (BHA) sag, drill string deformation, drill string bending, and proximity to magnetic components near the sensor location. By accounting for these variables, the system enhances the reliability of measurements taken during drilling, such as directional or formation evaluation data. The system may also compare predicted measurement quality against actual measurements to identify discrepancies or errors, allowing for real-time adjustments or corrections. This approach helps mitigate inaccuracies caused by mechanical stress, misalignment, or electromagnetic interference, ensuring more precise data for drilling decisions. The system integrates these quality assessments into a broader data processing framework, enabling operators to optimize drilling trajectories and formation analysis based on high-confidence measurements.
22. The system of claim 20 , wherein generating the first and second sets of performance data includes determining predicted measurement quality as a function of nearness to a borehole wall.
The system relates to oil and gas wellbore monitoring, specifically improving the accuracy of downhole measurements by accounting for proximity to the borehole wall. In wellbore operations, measurement tools often produce inaccurate or unreliable data when positioned too close to the borehole wall due to environmental interference or tool limitations. This system addresses this issue by generating performance data that evaluates measurement quality based on the tool's distance from the borehole wall. The system includes a downhole tool with sensors and a processing unit that collects measurement data from the wellbore. The processing unit generates two sets of performance data: one for measurements taken near the borehole wall and another for measurements taken farther away. The system determines predicted measurement quality by analyzing how close the tool is to the borehole wall, as proximity can degrade signal integrity or introduce noise. By separating and evaluating these datasets, the system improves the reliability of downhole measurements, allowing operators to make more informed decisions about wellbore conditions, fluid properties, or reservoir characteristics. The system may also include calibration mechanisms to adjust measurement parameters based on the predicted quality, ensuring consistent accuracy across varying distances from the borehole wall.
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September 3, 2019
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